A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.
Provides tools for interacting with SQL Server databases, enabling users to retrieve paginated table data, inspect schemas, and count records. It features enforced pagination and secure configuration options to manage database operations efficiently through natural language.
An MCP server for interacting with SQL Server databases that enables schema inspection, record counting, and paginated data retrieval. It provides tools to explore table structures and fetch specific records while enforcing safety limits on data volume.
A Model Context Protocol server for data wrangling that provides standardized interfaces for data preprocessing, transformation, and analysis tasks including data aggregation and descriptive statistics.
A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.
An AI-centric MCP server that enables automated Xilinx Vivado workflows, including project management, synthesis, implementation, and timing analysis. It allows AI agents to drive hardware design processes while integrating directly with the official Vivado GUI for visual context.
MCP server that launches Mesen/MesenCE headlessly and exposes the emulator's debugger-face Lua API over MCP JSON-RPC, enabling AI agents to load ROMs, step frames, inspect memory/registers, manage breakpoints/watches, trace execution, and export Code/Data Logger maps for SNES, NES, PC Engine, and Game Boy Advance.
Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.
A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.
MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.
Enables AI agents to access user and message data through MCP resources, providing REST API integration for user management with paginated lists and thread tracking.
An MCP Server that enables interaction with Google's Data Labeling API, allowing users to manage datasets, annotations, and labeling tasks through natural language commands.
An educational example demonstrating how to build MCP servers in Python using FastMCP, showing how to expose tools, resources, and prompts to AI clients.